Linking single cell genomes and transcriptomes at scale to decode breast cancer progression [scRNA-seq]

Understanding the epithelial lineages of breast cancer and genotype-phenotype relationships requires direct measurements of the genome and transcriptome of the same single cells at scale. To achieve this, we developed wellDR-seq, the first high-genomic resolution, high-throughput method to simultaneously profile the genome and transcriptome of thousands of single cells in parallel. We profiled 33,646 single cells from 12 estrogen receptor-positive breast cancers, and identified ancestral subclones in multiple patients that showed a luminal hormone responsive lineage, indicating a potential cell-of-origin. Our data also identified sporadic copy number aberrations (CNAs) in the two luminal epithelial lineages and stromal cells. While gene expression was highly correlated with copy number in larger chromosome segments, our data reveals extensive variation at the single gene-level, reflecting differences in dosage-sensitive and dosage-insensitive genes. Overall, these data reveal the complex relationships between CNAs and gene expression in single cancer cells, improving our understanding of breast cancer progression. We developed a high-genomic resolution, high-throughput nanowell single cell DNA & RNA sequencing method (wellDR-seq), that can simultaneously profile the whole genome and transcriptome from thousands of single cells. We first demonstrated wellDR-seq was capable of generating comparable data quality as unimodal scRNA-seq and scDNA-seq technologies using MDA-MB-231 cell line. We then applied it to profile 12 ER+ breast cancer patients, which identified ancestral cancer subclones and their epithelial lineages, normal epithelial cell states with somatic CNAs and revealed the impact of subclonal CNAs on gene dosage, providing insight into the complex relationship between DNA copy number and gene expression in cancer cells. Please note that the DNA raw data was deposited to SRA (PRJNA1086561).